Customer service representatives (CSRs) are the face of your brand; skilled and empowered reps are essential to improve customer experience and enhance consumer loyalty. Whether customers walk into a retail store where brand reps help them compare products, make recommendations and deliver a personalized sales experience — or speak to a call center agent to resolve an issue or assist with online purchase journeys, the experience delivered by CSRs is fundamental to brand success.
The challenge? Customer reps are under massive pressure to deliver exceptional service on-demand — like ducks on the water, they’re calm on the surface but paddling like mad underneath. According to recent AdWeek data, 52 percent of CSRs feel their company isn’t doing enough to prevent burnout and 35 percent are considering leaving their jobs. In the age of big data, personalized experience and rising consumer expectations, agents need a new best friend to help keep them afloat: Artificial intelligence (AI).
The challenge of staying afloat
Being a CSR isn’t easy. Agent attrition is steep — ranging from 30 to 45 percent — and on-boarding new staff to fill the gaps often causes dips in customer satisfaction. So why the churn? For customer care agents, it’s easy to end up overwhelmed and underwater. Some of their top challenges include:
◉ Lacking tools: 44 percent of CSRs say they lack the right tools, the AdWeek report found; 34 percent of contact center decision-makers say they don’t have access to knowledge management solutions, making it difficult to find, sort and leverage customer data on-demand.
◉ Missing data: 34 percent of respondents to the AdWeek study point to a lack of pertinent customer data, in turn frustrating their efforts to deliver a personalized experience.
◉ Increasing pressure: Call volumes have increased 39 percent in the last 18 months, AdWeek reports — and 92 percent of customers will stop buying from brands after three (or fewer) poor interactions. This puts massive pressure on agents to deliver delightful service with high first call resolution (FCR) rates.
◉ Siloed systems: Data systems are often disparate and difficult to access, meaning CSRs need to rapidly cycle through multiple applications to research the issue — resulting in longer hold times for customers.
◉ Limited context: Context is everything. Cold-start conversations and evolving product lines make it difficult to gauge exactly what consumers want on first contact, leaving CSRs stuck in a loop even as customers get frustrated having to repeat their concerns. A well informed acknowledgement of the issue in the opening greeting from the agent can set a positive tone for the rest of the interaction.
How AI can help
Artificial intelligence tools offer a way to bridge the gap between customer expectations and agent abilities. By leveraging intelligent tools capable of collating disparate data sources, analyzing consumer calls for context and delivering on-demand assistance to agents, there’s potential for companies to improve customer satisfaction scores (CSAT) by 20 to 30 points, and eliminate up to 30 percent of call center costs by implementing AI tools to assist agents. For large organizations handling 100 million+ calls each year, this could mean savings into the billions over time.
No fear: why agents want AI
Fear of AI takeover is dwindling; Tech Republic notes that just 27 percent of call center staff worry that AI will eliminate their jobs. Instead, agents want AI to help them where it matters most: Eliminating redundant processes. Meanwhile, Tech Republic also reports that 70 percent of agents believe that effective automation of routine tasks would allow them to focus on higher-value work. Put simply, human agents and AI working in tandem is the CSR dream.
In their personal lives, CSRs are increasingly exposed to delightful AI-augmented experiences via their mobile phones, such as auto-complete, tailored social media content, digital assistants and contextual personalized search. CSRs expect this same AI augmentation at work to improve their productivity.
Improving AI customer care with human input
More than 50 percent of call center managers recognize the need for new technology, but almost 60 percent highlight ongoing IT issues. This paradox emerges full-force when companies look to implement AI; despite big potential, new deployments don’t always improve customer experience as predicted. The problem? Missing input from the experts — your customer service reps.
While it’s tempting to offload everything to AI, many agents have in-depth knowledge of specific products, existing service models and customer-facing processes. The result? They don’t want AI to attempt to automate the entire workflow end-to-end. What agents really want are tools capable of collecting key consumer data up front, automating some mundane simple tasks and offering help and recommendations to agents when appropriate. Put simply, this isn’t an all-or-nothing scenario: When AI and human agents work as a team, they can split individual tasks of the workflow.
Clients across industries have partnered with IBM to deploy five key approaches for effective AI-agent teaming. Stay tuned for our upcoming second piece in this AI series to be published shortly.
Source: ibm.com
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